A throughflow-based optimization method for multi-stage axial compressor

A multi-objective optimization tool for multi-stage axial compressors is developed based on an automatically calibrated throughflow method. The Euler-based throughflow equations with blade force terms are solved using a time-marching finite volume method to obtain the meridional flow fields, while the traditional empirical deviation and loss correlation are substituted by several Kriging metal models constructed based on the circumferentially averaged results of three-dimensional computational fluid dynamics simulations. Optimization maximizing both the total pressure ratio and adiabatic efficiency is performed to search for the optimal flowpath and radial distributions of geometrical parameters by using the non-dominated sorted genetic algorithm II method. A low-speed 4.5-stage axial compressor is chosen as the test case to verify the procedures, including throughflow solver validation, design optimization, etc. The throughflow solver has proved to be reliable. The optimization under the design operation condition achieves a great increase in the total pressure ratio and a small increase in adiabatic efficiency. Moreover, improvements in the total pressure ratio and stall margin are also observed for the optimal configuration in this optimization, with a decrease in the cost of adiabatic efficiency under the operation condition near stall.